Colorectal cancer is the second leading cause of cancer-related deaths in the United States. Most colorectal cancers are believed to arise within benign adenomatous polyps that develop slowly over the course of many years. Accepted guidelines recommend the screening of adults who are at average risk for colorectal cancer, since the detection and removal of adenomas has been shown to reduce the incidence of cancer and cancer-related mortality. Some researchers have advocated screening programs to detect polyps with a diameter of less than one centimeter. Unfortunately, most people do not follow this advice because of the discomfort and inconvenience of the traditional optical colonoscopy. To encourage people to participate in screening programs, virtual colonoscopy (VC), also known as computed tomographic colonography (CTC), has been proposed and developed to detect colorectal neoplasms by using a computed tomography (CT) or MRI scan. Virtual colonoscopy is minimally invasive and does not require sedation or the insertion of a colonoscope. Virtual colonoscopy exploits computers to reconstruct a 3D model of the CT scans taken of the patient's abdomen, and create a virtual fly through of the colon to help radiologists navigate the model and make an accurate and efficient diagnosis. Previously known systems and methods for performing virtual colonoscopy are described, for example, in U.S. Pat. Nos. 5,971,767, 6,331,116 and 6,514,082, the disclosures of which are incorporated by reference in their entireties.
It has been demonstrated that the performance of a virtual colonoscopy compares favorably with that of a traditional optical colonoscopy. However, because of the complicated geometric and topological structure of colon models, inspecting the whole colon can be time consuming and prone to perceptual errors. For example, a single examination can typically generate 400-700 512×512 CT images and may require 10-15 minutes to be interpreted. The large amount of interpretation effort involved in the virtual colonoscopy screening procedure make a computer-aided detection (CAD) scheme highly desirable.
A CAD scheme that automatically detects the locations of the potential polyp candidates could substantially reduce the radiologists' interpretation time and increase their diagnostic performance with higher accuracy. However, the automatic detection of colonic polyps is a very challenging task because the polyps can have various sizes and shapes. Moreover, false positives (FPs) can arise since the colon exhibits numerous folds and residual colonic materials on the colon wall often have characteristics that mimic polyps. A practical CAD scheme for clinical purposes should have the ability to identify the true polyps and effectively eliminate or at least substantially reduce the number of false-positives.
It has been reported that the internal tissues of polyps have a slightly higher density and different texture than healthy tissues. See “Interactive Electronic Biopsy for 3d Virtual colonoscopy,” Wan et al., SPIE Medical Imaging 4321: 483-488, 2001, the disclosure of which is hereby incorporated by reference in its entirety. However, these high density areas reside beneath the colon wall and cannot be seen during optical colonoscopy and are not identified in surface rendered virtual colonoscopy. It would be desirable to be able to use the increased sub-surface density characteristics of a polyp to provide improved CAD results.